Imaging the brain's activity in various states is important to get a more accurate picture of how depression manifests in a particular patient.
Thermo Scientific Avizo2D is an AI-powered automated imaging and analysis software designed to help materials and life science researchers acquire fast statistics from their electron microscopy (EM) images without extensive image processing expertise.
As a central facility for storing blood and tissue samples, the Auckland Region Tissue Bank has a library that could hold the secrets to unlocking cures for chronic diseases and illnesses.
Bitplane's Imaris 9.3 is a software solution for correlative microscopy, enabling the possibility of opening multiple 2D, 3D or 4D datasets of differing spatial and temporal resolutions in the same scene.
While striving to remain on the cutting edge of scientific discovery, researchers need more agile and powerful computing in order to drive towards a better future for everyone.
A laboratory test using artificial intelligence tools has the potential to more accurately sort out which people with pancreatic cysts will go on to develop pancreatic cancers.
An international challenge compared the diagnostic skills of 511 physicians with 139 computer algorithms from 77 different machine learnings labs.
Two separate sets of European researchers have developed their own artificial intelligence methods to identify rare diseases, for which obtaining a definitive diagnosis can be difficult and time-consuming.
A multi-institutional, multimillion-dollar project to understand how antimicrobial-resistant bacteria spread, and to develop new ways to combat it, has won a $1 million grant.
Sartorius Stedim Data Analytics has announced SIMCA 16 software for multivariate data analytics. The updated SIMCA focuses on delivering a complete data analysis experience, from data organisation through to data-driven decision-making, supported by multivariate models for single and multiblock analysis.
German researchers are currently involved in an interdisciplinary and multi-institutional project aimed at making automated diagnoses from a software program more transparent.
Developed by start-up company Lookinglass, the app is designed to reduce the number of physical appointments required with doctors and occupational therapists.